Where do we begin as we analyse mobility patterns? Do we look at economics? Behavioural psychology? Sociology? Urban planning? Marketing?
What if we took all of these diverse approaches, threw them into a blender, and then added a pinch of strategic foresight before serving it up to policymakers, researchers, transport providers and the wider public?
“Digital information is the fuel of the future mobility. The car will become an accessory to the smartphone.”
– Gilles Vesco
The MIND-SETS concept, which was tested by experts in the next phase of the project (see Testing the MIND-SETS concept), was based on an interdisciplinary analysis of existing knowledge.
This analysis was broken down into the following tasks:
Factors that influence mobility behaviour
It is essential to consider several factors in the implementation of new policies, and therefore we coordinated knowledge from different fields that approach the mobility issue from a wide range of perspectives.
Economic drivers and barriers
The economic approach to travel behaviour underpins numerous models that are used in planning practice and policy. The focus here was on the behavioural assumptions underlying the models in the peer-reviewed literature, with a focus on the “rational actor” assumption and the equilibrium concepts. Our discussion concentrated on the demand side of transport.
Psychological drivers and barriers
The goal of this task was to focus on existing literature to enhance our understanding of the psychological factors determining mobility patterns and of the psychological value of mobility for individuals with different lifestyles. Our review covered four main topics:
- The role of psychological factors, such as values and habits (Verplanken et al., 1997; 1998);
- The role of motivational factors, such as perceived effort, cost and benefits of mobility services and how they affect travel behaviour (see Dijst et al., 2013);
- The effect of social factors, such as lifestyle orientations or perceived status associated with certain mobility patterns and transport behaviours (e.g., car-ownership vs. using public transport; Steg, 2005);
- The psychological value of mobility; such as promoting well-being and quality of life (Ryan & Deci, 2000).
Social drivers and barriers
This task analysed the social drivers and barriers that determine the mobility patterns of different social groups. It looked at mobility both as a determinant and a reflection of lifestyle types and considered trends such as breaking from conformity, constraints on activity patterns and mobility barriers (frailty and dependency, sensory, ambient and mental disabilities, low income levels, gender roles, ethnicity and religious beliefs).
The role of emerging technologies
This review identified current technological trends and analysed existing knowledge on how these trends affect travel behaviour. We focused on the following areas:
• The impact of ICT social networks and new social media on travel behaviour;
• Transportation-telecommunications relationships (i.e teleworking, teleshopping);
• Urban forms and the built environment;
• The impact of new vehicle technologies and new infrastructure on travel behaviour;
• The use of social media in public transportation;
• Data characteristics applied to current transportation models.
The influence of geography, borders, culture and language
We explored how spatial dynamics influence long-distance mobility patterns – both in different areas of Europe and chunks of territory within these areas – using a number of representative case-studies. The analysis consisted in comparing existing data provided at the European level to other, more detailed sources of information. We explored the contemporary meanings of “distance” and “place”, and elaborated the result as “Mobility mind-sets mapped out across Europe”.
Indications to refine and update urban and European transport models were developed with regard to aspects such as:
• The use of different modes at the national level in European countries;
• The use of different modes in cities of different size categories in each country;
• Changing patterns of long distance ‘European’ mobility in the air and rail sectors.
Longer term influences on mobility decisions
For planning purposes, public authorities typically extrapolate how transport demand has evolved in the past as a function of socio-economic variables. Here, we verified whether this approach is justified – for instance, it has been argued that traditional forecasting models have failed to capture that senior “baby boomers” would have fundamentally different lifestyles than their predecessors.
People’s mobility horizons, networks and mental maps
Here, we considered activity spaces, action spaces, awareness spaces and virtual spaces, relating to the local, regional, national and international worlds.
Meeting future mobility needs
Future mobility lifestyles: defining the needs of users
Broad socio-demographic trends are likely to affect future travel needs. Given that attitudinal variables often surpass traditional socio-economic and demographic variables in terms of explaining travel behaviour, we took a closer look at probable future developments in attitudes and values.
New mobility products, services and systems
Specific mobility products, services and systems will be needed to satisfy the user needs identified above. We compared these to current and planned mobility products, services and systems to identify any gaps.
New professional practices to maximise innovation, meet needs and protect workers
New business models to meet user needs can also impact labour relations. For instance, new firms such as Uber provide “taxi-like” services using web-based reservation schemes. These services are highly popular where they are introduced, but they have had a profound impact on the existing taxi industry.
After formulating a set of ideas regarding people’s shifting attitudes towards mobility, we put these ideas to the test.